





import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase	,_lowerCAmelCase	,_lowerCAmelCase	,_lowerCAmelCase=True	,_lowerCAmelCase="pt"  ):
   '''simple docstring'''


   A_  :					Tuple         =						{"""add_prefix_space""": True} if isinstance(_A	,_A  ) and not line.startswith(""" """  ) else {}
   A_  :					Union[str, Any]         =						padding_side
   return tokenizer(
       [line]	,max_length=_A	,padding="""max_length""" if pad_to_max_length else None	,truncation=_A	,return_tensors=_A	,add_special_tokens=_A	,**_A	,)



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase	,_lowerCAmelCase=None	,):
   '''simple docstring'''


   A_  :					Optional[Any]         =						input_ids.ne(_A  ).any(dim=0  )
   if attention_mask is None:
      return input_ids[:, keep_column_mask]
   else:
      return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])

class  _UpperCAmelCase				(		_UpperCAmelCase  ):
      def __init__(		self   ,							a__   ,							a__   ,							a__   ,							a__   ,							a__="train"   ,							a__=None   ,							a__=None   ,							a__=None   ,							a__=""   ,							):
         super().__init__()
         A_  :					List[Any]         =						Path(__UpperCamelCase							).joinpath(type_path + """.source"""							)
         A_  :					Union[str, Any]         =						Path(__UpperCamelCase							).joinpath(type_path + """.target"""							)
         A_  :					Dict         =						self.get_char_lens(self.src_file							)
         A_  :					List[str]         =						max_source_length
         A_  :					Dict         =						max_target_length
         assert min(self.src_lens							) > 0, F"""found empty line in {self.src_file}"""
         A_  :					Union[str, Any]         =						tokenizer
         A_  :					Tuple         =						prefix
         if n_obs is not None:
            A_  :					Any         =						self.src_lens[:n_obs]
         A_  :					Dict         =						src_lang
         A_  :					str         =						tgt_lang
      def __len__(		self							):
         return len(self.src_lens							)
      def __getitem__(		self   ,							a__							):
         A_  :					Optional[int]         =						index + 1  # linecache starts at 1
         A_  :					str         =						self.prefix + linecache.getline(str(self.src_file							)   ,							__UpperCamelCase							).rstrip("""\n"""							)
         A_  :					Tuple         =						linecache.getline(str(self.tgt_file							)   ,							__UpperCamelCase							).rstrip("""\n"""							)
         assert source_line, F"""empty source line for index {index}"""
         assert tgt_line, F"""empty tgt line for index {index}"""

         # Need to add eos token manually for T5
         if isinstance(self.tokenizer   ,							__UpperCamelCase							):
            source_line += self.tokenizer.eos_token
            tgt_line += self.tokenizer.eos_token

         # Pad source and target to the right
         A_  :					Optional[Any]         =						(
             self.tokenizer.question_encoder if isinstance(self.tokenizer   ,							__UpperCamelCase							) else self.tokenizer
         )
         A_  :					List[str]         =						self.tokenizer.generator if isinstance(self.tokenizer   ,							__UpperCamelCase							) else self.tokenizer

         A_  :					Any         =						encode_line(__UpperCamelCase   ,							__UpperCamelCase   ,							self.max_source_length   ,							"""right"""							)
         A_  :					Any         =						encode_line(__UpperCamelCase   ,							__UpperCamelCase   ,							self.max_target_length   ,							"""right"""							)

         A_  :					List[Any]         =						source_inputs["""input_ids"""].squeeze()
         A_  :					List[str]         =						target_inputs["""input_ids"""].squeeze()
         A_  :					int         =						source_inputs["""attention_mask"""].squeeze()
         return {
             "input_ids": source_ids,
             "attention_mask": src_mask,
             "decoder_input_ids": target_ids,
         }
      @staticmethod
      def 		_lowerCamelCase   (		a__							):
         return [len(__UpperCamelCase							) for x in Path(__UpperCamelCase							).open().readlines()]






      def 		_lowerCamelCase   (		self   ,							a__							):
         A_  :					Tuple         =						torch.stack([x["""input_ids"""] for x in batch]							)
         A_  :					int         =						torch.stack([x["""attention_mask"""] for x in batch]							)
         A_  :					List[Any]         =						torch.stack([x["""decoder_input_ids"""] for x in batch]							)
         A_  :					Dict         =						(
             self.tokenizer.generator.pad_token_id
             if isinstance(self.tokenizer   ,							__UpperCamelCase							)
             else self.tokenizer.pad_token_id
         )
         A_  :					Dict         =						(
             self.tokenizer.question_encoder.pad_token_id
             if isinstance(self.tokenizer   ,							__UpperCamelCase							)
             else self.tokenizer.pad_token_id
         )
         A_  :					Tuple         =						trim_batch(__UpperCamelCase   ,							__UpperCamelCase							)
         A_   ,					A_  :					List[str]         =						trim_batch(__UpperCamelCase   ,							__UpperCamelCase   ,							attention_mask=__UpperCamelCase							)
         A_  :					Union[str, Any]         =						{
             """input_ids""": source_ids,
             """attention_mask""": source_mask,
             """decoder_input_ids""": y,
         }
         return batch






_lowerCAmelCase								=  getLogger(__name__)



def      _lowerCAmelCase		(	_lowerCAmelCase  ):
   '''simple docstring'''


   return list(itertools.chain.from_iterable(_A  )  )



def      _lowerCAmelCase		(	_lowerCAmelCase  ):
   '''simple docstring'''


   A_  :					Any         =						get_git_info()
   save_json(_A	,os.path.join(_A	,"""git_log.json"""  )  )



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase	,_lowerCAmelCase=4	,**_lowerCAmelCase  ):
   '''simple docstring'''


   with open(_A	,"""w"""  ) as f:
      json.dump(_A	,_A	,indent=_A	,**_A  )



def      _lowerCAmelCase		(	_lowerCAmelCase  ):
   '''simple docstring'''


   with open(_A  ) as f:
      return json.load(_A  )



def      _lowerCAmelCase		(	):
   '''simple docstring'''


   A_  :					List[Any]         =						git.Repo(search_parent_directories=_A  )
   A_  :					Optional[Any]         =						{
       """repo_id""": str(_A  ),
       """repo_sha""": str(repo.head.object.hexsha  ),
       """repo_branch""": str(repo.active_branch  ),
       """hostname""": str(socket.gethostname()  ),
   }
   return repo_infos



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase  ):
   '''simple docstring'''


   return list(map(_A	,_A  )  )



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase  ):
   '''simple docstring'''


   with open(_A	,"""wb"""  ) as f:
      return pickle.dump(_A	,_A  )



def      _lowerCAmelCase		(	_lowerCAmelCase  ):
   '''simple docstring'''


   def remove_articles(_lowerCAmelCase  ):
      return re.sub(r"""\b(a|an|the)\b"""	,""" """	,_A  )

   def white_space_fix(_lowerCAmelCase  ):
      return " ".join(text.split()  )

   def remove_punc(_lowerCAmelCase  ):
      A_  :					Tuple         =						set(string.punctuation  )
      return "".join(ch for ch in text if ch not in exclude  )

   def lower(_lowerCAmelCase  ):
      return text.lower()

   return white_space_fix(remove_articles(remove_punc(lower(_A  )  )  )  )



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase  ):
   '''simple docstring'''


   A_  :					str         =						normalize_answer(_A  ).split()
   A_  :					List[str]         =						normalize_answer(_A  ).split()
   A_  :					Any         =						Counter(_A  ) & Counter(_A  )
   A_  :					int         =						sum(common.values()  )
   if num_same == 0:
      return 0
   A_  :					str         =						1.0 * num_same / len(_A  )
   A_  :					Any         =						1.0 * num_same / len(_A  )
   A_  :					int         =						(2 * precision * recall) / (precision + recall)
   return fa



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase  ):
   '''simple docstring'''


   return normalize_answer(_A  ) == normalize_answer(_A  )



def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase  ):
   '''simple docstring'''


   assert len(_A  ) == len(_A  )
   A_  :					Optional[Any]         =						0
   for hypo, pred in zip(_A	,_A  ):
      em += exact_match_score(_A	,_A  )
   if len(_A  ) > 0:
      em /= len(_A  )
   return {"em": em}



def      _lowerCAmelCase		(	_lowerCAmelCase  ):
   '''simple docstring'''


   return model_prefix.startswith("""rag"""  )







def      _lowerCAmelCase		(	_lowerCAmelCase	,_lowerCAmelCase	,_lowerCAmelCase  ):
   '''simple docstring'''


   A_  :					Optional[Any]         =						{p: p for p in extra_params}
   # T5 models don't have `dropout` param, they have `dropout_rate` instead
   A_  :					List[Any]         =						"""dropout_rate"""
   for p in extra_params:
      if getattr(_A	,_A	,_A  ):
         if not hasattr(_A	,_A  ) and not hasattr(_A	,equivalent_param[p]  ):
            logger.info("""config doesn't have a `{}` attribute""".format(_A  )  )
            delattr(_A	,_A  )
            continue
         A_  :					Optional[int]         =						p if hasattr(_A	,_A  ) else equivalent_param[p]
         setattr(_A	,_A	,getattr(_A	,_A  )  )
         delattr(_A	,_A  )
   return hparams, config








"""simple docstring"""



import warnings
from functools import wraps
from typing import Callable


def 			_UpperCamelCase						(    _A   )     ->	Callable:





    """simple docstring"""

    @wraps(_A   )
    def _inner_fn(*_A       ,   **_A   ):
        warnings.warn(
            (F"""'{fn.__name__}' is experimental and might be subject to breaking changes in the future.""")       ,   _A       ,   )
        return fn(*_A       ,   **_A   )

    return _inner_fn